Methods, Systems, Devices, and Products for Authenticating Users

ABSTRACT

Enhanced biometric authentication combines a user&#39;s inherent biometric data with the user&#39;s password, code, or other secret glyph. For example, the user&#39;s finger makes an input on a touchpad. An image of a fingerprint is extracted from the input, along with the user&#39;s password, code, or other secret glyph. In one input, then, the user&#39;s finger serves two authentication schemes for increased security.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser.No.13/737,984 filed Jan. 10, 2013 and now issued as U.S. Pat. No.______, which is a continuation of U.S. application Ser. No. 12/537,949filed Aug. 7, 2009 and now issued as U.S. Pat. No. 8,384,514, with bothapplications incorporated herein by reference in their entireties

BACKGROUND

1. Field of the Disclosure

The present invention relates to the field of biometric authenticationand more particularly to an enhanced device and process for biometricauthentication.

2. Description of the Related Art

A concern with any security system is authentication, i.e., grantingaccess to authorized persons and denying access to unauthorized persons.Successful authentication occurs when a system correctly determines thata user is who he claims to be, usually by the user providing at leastone self-identifying security token. Many electronic systems will use aperson's knowledge, for example of a password, as a security token.Increased security may also be achieved by requiring as a tokensomething in the user's possession, such as a digital certificate. Somesecurity systems will use biometric data, such as fingerprints orretinal scans, as a security token.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of selected elements of an exemplaryembodiment of an enhanced biometric authentication device;

FIG. 2 is a block diagram of selected elements of a fingerprint scannerprovided as one exemplary embodiment of an input sensor;

FIG. 3 depicts selected elements of an exemplary embodiment of abiometric processing engine;

FIG. 4 depicts selected elements of an exemplary embodiment of amechanics processing engine;

FIG. 5 depicts selected elements of an exemplary embodiment of anauthentication engine;

FIG. 6 is a diagram of a fingerprint touch pad disclosing an exemplarycomposite input sample provided as a security token;

FIG. 7 is a diagram of a fingerprint touchpad providing a secondexemplary security token input sample;

FIG. 8 is a diagram of a plurality of fingerprint touch pads, disclosinga third exemplary security token input sample; and

FIGS. 9A, 9B, and 9C are diagrams of a single fingerprint touch pad usedto enter a string of alphanumeric characters in sequence.

DESCRIPTION OF THE EMBODIMENT(S)

In one aspect, a disclosed method for achieving enhanced biometricauthentication includes combining a user's inherent biometric data withthe user's knowledge of a secret pattern. A touchpad may be provided onwhich the user may use a finger to perform a plurality of strokes thatform a distinct pattern. Image stabilization may be used to extract areadable fingerprint from the strokes. The pattern and finger print arematched to a stored profile. A user may train a device to recognizewritten letters. The user can then enter a password on a touch pad withhis finger. If the fingerprint and password both match, the user isauthenticated.

In the following description, details are set forth by way of example tofacilitate discussion of the disclosed subject matter. It should beapparent to a person of ordinary skill in the field, however, that thedisclosed embodiments are exemplary and not exhaustive of all possibleembodiments. Throughout this disclosure, a hyphenated form of areference numeral refers to a specific instance of an element and theun-hyphenated form of the reference numeral refers to the elementgenerically or collectively. Thus, for example, widget 12-1 refers to aninstance of a widget class, which may be referred to collectively aswidgets 12 and any one of which may be referred to generically as awidget 12.

FIG. 1 is a block diagram disclosing an exemplary embodiment of anenhanced biometric authentication device 100 in operation. In FIG. 1,elements of authentication device 100 are shown in rectangular blockswhile data that is provided to or processed by authentication device 100is shown in oval blocks. In the disclosed embodiment, a composite input120 is provided to an input sensor 110. Composite input 120 includes abiometric component 112 and a mechanical component 114. The biometriccomponent 112 may be one of numerous physiological biometric indicatorsknown in the art, such as finger print, hand print, facial scan, retinalscan, body chemistry, or DNA analysis. To facilitate discussion, theexamples in this specification will use a fingerprint as an example, butpersons of ordinary skill in the art will recognize, in light of thisspecification, that other biometric indicators can be adapted to thedisclosed devices and techniques. Mechanical component 114 may includeany combination of mechanical indicators, such as position, motion,time, direction, velocity, pressure, and acceleration. By way ofnon-limiting example, composite input 120 could include a finger tracinga glyph, wherein the biometric component 112 comprises a finger printand mechanical component 114 comprises the tracing motion; or compositeinput 120 could include a person moving his or her eyes, where thebiometric component 112 comprises a retinal scan and mechanicalcomponent 114 comprises the motion of the eyes. Input sensor 110 isoperable to segregate or otherwise distinguish biometric component 112and mechanical component 114.

Mechanical component 114 is provided to a mechanics processing engine140, which creates a mechanical characterization 142. Similarly,biometric component 112 is provided to a biometric processing engine130, which creates a biometric characterization 132. In someembodiments, a characterization is a reduced profile or other type ofrepresentation of the raw data contained in the composite input 120.Profile reduction may be accomplished, for example, by a heuristic modelor by any of the other numerous methods known in the art for matchingbiometric data.

The characterizations 132, 142 are provided to an authentication engine150, which also receives an authentication template 160. Anauthentication template 160 is a stored characterization profile,containing both a mechanical component 164 and a biometric component162. Authentication template 160 may be generated in advance of theattempted authentication. There may also be a tolerance 152 associatedwith authentication template 160. Tolerance 152 may indicate the degreeof allowable difference between characterizations 132, 142 and thecorresponding components 162, 164.

Authentication engine 150 compares characterizations 132, 142 tocomponents 162, 164 of authentication template 160. If bothcharacterizations match the respective components of authenticationtemplate 160 within tolerance 152, the user is authenticated, and anauthentication 170 is provided. In some cases, feedback 180 may also beprovided to indicate whether or not the user was successfullyauthenticated.

FIG. 2 is a block diagram of selected elements of a fingerprint scanner110-1 provided as an exemplary implementation of an input sensor 110.Persons of skill in the art will recognize that alternative fingerprintscanners, as well as other biometric input sensors, may be suitable forthe same function. In the disclosed embodiment, a touch surface 210provides an interface for receiving composite input 120. A sensor array220 reads the fingerprint using a fingerprint scanning technology,several of which are known in the art. For example, optical, capacitive,and ultrasonic type sensors are all known in the art. A transducer 230digitizes the composite input 120 and provides digital data to apre-processor 240. Pre-processor 240 is powered by power source 250,which also may provide power to transducer 230 as necessary to implementthe fingerprint scanning technology. A clock 270 is also provided toenable pre-processor 240 to handle timing issues related to capturing amechanical component of composite input 120. Pre-processor 240 processesthe digital data to generate mechanical component 114 and biometriccomponent 112. In the depicted embodiment, pre-processor 240 may haveaccess to processor executable instructions that comprise apre-processing algorithm 262. As depicted in FIG. 2, pre-processingalgorithm 262 is stored in a memory 260 that is accessible topre-processor 240.

FIG. 3 is an exemplary embodiment of a biometric processing engine 130.Biometric processing engine 130 receives biometric component 112 frominput sensor 110 (FIG. 1). A biometrics processor 340 is provided tohandle the necessary processing. While shown separately, persons havingskill in the art will recognize that the disclosure describes functionaldistinctions, but that biometrics processor 340 may be a single physicaldevice with some or all of pre-processor 240 (FIG. 2), mechanicsprocessor 440 (FIG. 4), and processor 540 (FIG. 5). Biometrics processor340 is communicatively coupled to memory 360, which also may be a singlephysical device with any or all of memory 260 (FIG. 2), memory 460 (FIG.4), memory 560 (FIG. 5). Memory 360 as shown includes instructions thatprovide a characterization algorithm 362, which provides a method forcharacterizing biometric component 112. Many such algorithms are knownin the art. For example, U.S. Pat. No. 6,963,659 issued to Tumey, et al.on Nov. 8, 2005 discloses a heuristic algorithm for fingerprintmatching.

Because composite input 120 includes a mechanical component 114 (FIG.1), an image stabilizer 342 may be desirable or required to permitbiometric processing engine 130 to extract a usable biometric sample.Image stabilizer 342 may employ a technique such as extracting a singleframe from a high-frequency composite input sample so as to provide asteady-state image of the biometric component, or a reasonableapproximation thereof. Image stabilizer 342 may also provide additionalsharpening or other processing as necessary to clean up residual blur orother artifacts created by mechanical inputs. Persons of skill in theart will recognize that, while image stabilizer 342 is shown as part ofbiometrics processing engine 130, some or all of the functionality couldalso be provided in input sensor 110 as necessary to suit a particularimplementation.

Characterization algorithm 362 creates a biometric characterization 132of biometric component 112 and provides biometric characterization 132as an output. In the case of a fingerprint, for example, the biometriccharacterization 132 generated by characterization algorithm 362 mayinclude data representative of or indicative of the fingerprint. Thedata may be compliant with a standardized format for representingfingerprints.

FIG. 4 is a block diagram disclosing an exemplary embodiment of amechanics processing engine 140. As described above, mechanicsprocessing engine 140 may share some or all of its hardware withbiometrics processing engine 130 and authentication engine 150.Mechanics processing engine 140 receives mechanical component 114 as aninput. Mechanics processing engine 140 as shown includes mechanicsprocessor 440 connected to memory 460, in which is stored instructionsthat provide a mechanical characterization algorithm 462.Characterization algorithm 462 may provide any one of numerous possiblealgorithms, depending on the specific implementation. For example, insome embodiments, mechanical component 114 may describe an arbitraryglyph designated by the user (see, for example, FIG. 6). As used in thisspecification, a glyph is any symbolic figure or character that conveysinformation non-verbally. In that case, mechanical component 114 maycontain such information as the number of strokes, the order of thestrokes, the location of the strokes on the touch pad 110-1, theorientation or direction of the strokes. This information may beconveyed, for example, by indicating the beginning and ending locationof each stroke. In some embodiments, touch pad 110-1 may be divided intosectors, as shown in FIG. 6, and location information may includeinformation such as the sector in which the stroke was begun, sectorsthe stroke traversed in which order, and the sector in which the strokeended. Mechanics processor 440 invokes characterization algorithm 462 togenerate a mechanical characterization 142, which is an output ofmechanics processing engine 140.

FIG. 5 is a block diagram of an exemplary embodiment of anauthentication engine 150, which as described above may share some orall of its hardware with input sensor 110, mechanics processing engine140, and/or biometric processing engine 130. Authentication engine 150receives biometric characterization 132 and mechanical characterization142. An authentication template 160 may be stored in non-volatilestorage and also provided to authentication engine 150. Anauthentication processor 540 is connected to a memory 560. Memory 560includes instructions that provide a glyph matching algorithm 530. Glyphmatching algorithm 530 compares biometric characterization 132 andmechanical characterization 142 to authentication template 160 whichincludes a biometric component 162 and a mechanical component 164. Forglyph matching algorithm 530 to indicate a good match, both biometriccharacterization 132 and mechanical characterization 142 must match datain authentication template 160. If glyph matching algorithm 530indicates a match, then authentication processor 540 generatesauthentication 170.

FIG. 6 is a diagram of a fingerprint touch pad 110 indicating anexemplary composite input 120 provided as a security token. In thisexample, the composite input 120 includes a three-stroke glyph drawn bythe user's index finger. The first stroke 611 is drawn by starting insector 1 and, in a substantially straight downward motion, traversingsector 4 and ending in sector 7. The second stroke 612 is drawn startingin sector 2, traversing sector 4 in a downward and left diagonal motion,and ending in sector 6. The third stroke 613 is made by starting insector 3, traversing sector 4 in a rightward horizontal motion, andending in sector 5. In this example, the foregoing data are stored in anauthentication template 160 along with a sample of the user'sfingerprint during a template creation process or procedure. When a userlater attempts to authenticate, biometric processing engine 130 willtake one or more samples of the user's fingerprint from touch pad 110and authentication engine 150 will determine whether there is a matchwith the fingerprint data in authentication template 160. Mechanicsprocessing engine 140 may provide data about the order and shape of thestrokes, including information such as the starting sector, endingsector, sectors traversed, and general direction. Authentication engine150 may determine whether these data match mechanical data in theauthentication template 160. If both the fingerprint and the mechanicaldata match biometric component 162 and mechanical component 164 in theauthentication template 160, the user may be authenticated.

FIG. 7 illustrates a second example of providing authentication via atouch pad 110. In FIG. 7, the user traces a glyph that lookssubstantially like a letter “Z.” Authentication template 160 could storestroke data such as in FIG. 6, in which case the order and shape of thestrokes may need to be matched to provide authentication. But as analternative, mechanics processing engine 140 characterization algorithm462 may include a handwriting recognition component that recognizesalphanumeric characters and, optionally, user specific characteristicsof one or more alphanumeric characters. In that case, mechanicsprocessing engine 140 may only provide, for example, the ASCII code forthe letter “Z,” and possibly additional data representing user specificcharacteristics of the input. Authentication template 160 would likewisecontain only the ASCII code for the letter “Z” in its mechanical dataand possibly a user specific data if needed. This method may simplifyauthentication for the user. Rather than having to remember the specificstrokes, including starting and ending sectors, the user would only needto remember a letter. On the other hand, this method may be less securethan the method of FIG. 6, as alphanumeric characters comprise arelatively small, bounded set.

In one embodiment, a user trains biometric authentication device 100with sample inputs of a plurality of glyphs. Authentication may thencomprise a step of presenting the user with one or morerandomly-selected glyphs and receiving a composite input 120corresponding to each glyph. Advantageously, this may pose difficultiesfor a non-authentic user, because he cannot learn a password as part ofcomposite input 120.

FIG. 8 is a diagram of a plurality of fingerprint touch pads 110, whichmay provide additional security over the method of FIG. 7. In thisexample, three touch pads 110-1, 110-2, and 110-3 are provided. The usermay choose a random three-character alphanumeric string such as “CTR”for authentication. In this case, “C” input 120-1 is entered on firsttouch pad 110-1, “T” input 120-2 is entered on second touch pad 120-2,and “R” input 120-3 is entered on third touch pad 110-3. The user isauthenticated only if those three letters are entered on those pads inthat order. To further enhance security, users may be required to usethe pads in a non-sequential order. For example, instead of entering theletters in the order “C” “T” “R,” the user may enter the letters on thetouch pads as disclosed, but in the order “T” “C” “R.” This provides theadditional security measure of requiring the user to know not only theletters to be entered on each pad, but the order in which the lettersare to be entered.

FIGS. 9A, 9B, and 9C are diagrams of a single fingerprint touch pad 110used to enter a string of alphanumeric characters. In this case, theuser chooses the pass phrase “C” “T” “R” as before. Rather than enteringthe letters on three separate touch pads, the user enters the letterssequentially on a single touch pad 110. This method provides the addedbenefit of allowing a pass phrase of arbitrary length and reduceshardware costs by employing just a single touchpad 110. For example,rather than the short phrase “CTR,” the user may choose as his passphrase a longer random string, including non-alphanumeric characters,such as “PTu7%5x”. This method provides the ability to use the same typeof pass phrase that is commonly used in the art, but with the addedsecurity measure that the pass phrase must be entered with a fingermatching the fingerprint stored in authentication template 160. Anotheradvantage to the use of pass phrases is that hashing algorithms may beemployed so that authentication template 160 need not store mechanicaldata in a format that would be accessible if authentication template 160itself were compromised. For example, if authentication template 160contained the string “PTu7%5x,” a malicious user who gains access toauthentication template 160 would learn the pass phrase portion ofauthentication template 160. Not only would this weaken the security ofenhanced biometric authentication device 100, but it may also weakensecurity for other systems, as many users re-use their passwords onmultiple systems. But if authentication template 160 stores only a hashof the pass phrase, then a malicious user would not learn any usefuldata, even if he gained access to authentication template 160. Anotherpotential solution is to store mechanical component 164 of template 160in a machine-usable form, and then to use biometric characterization 132as an encryption key to encrypt mechanical component 164. Thus,mechanical component 164 can only be decrypted for use with a correctbiometric characterization.

In one exemplary application of the method of FIG. 9, a laptop ordesktop computer could include a mouse pad that also includesfingerprint-sensing technology. When the user logs in, he will “write”his pass phrase, one character at a time, on the mouse pad. The userwill be authenticated only if both the pass phrase and the user'sfingerprint match, as determined by a finger print matching algorithmand a hash function performed on the pass phrase.

To the maximum extent allowed by law, the scope of the presentdisclosure is to be determined by the broadest permissibleinterpretation of the following claims and their equivalents, and shallnot be restricted or limited to the specific embodiments described inthe foregoing detailed description.

1. A method, comprising: receiving, by a server, an input sent from adevice for authentication; segregating, by the server, the input into animage of a fingerprint and a mechanical component; determining, by theserver, a match between the image of the fingerprint and a template forthe authentication; determining, by the server, the match between themechanical component and the template for the authentication; andauthenticating, by the server, the device in response to the match. 2.The method of claim 1, further comprising determining a password as themechanical component.
 3. The method of claim 1, further comprisingdetermining a trace as the mechanical component.
 4. The method of claim1, further comprising determining a character as the mechanicalcomponent.
 5. The method of claim 1, further comprising determining acombination of characters as the mechanical component.
 6. The method ofclaim 1, further comprising determining a letter as the mechanicalcomponent.
 7. The method of claim 1, further comprising determining astroke as the mechanical component.
 8. A system, comprising: aprocessor; and a memory storing instructions that when executed causethe processor to perform operations, the operations comprising:receiving an input sent from a device for authentication; segregatingthe input into an image of a fingerprint and a mechanical component;determining a match between the image of the fingerprint and a templatefor the authentication; determining the match between the mechanicalcomponent and the template for the authentication; and authenticatingthe device in response to the match.
 9. The system of claim 8, whereinthe operations further comprise determining a password as the mechanicalcomponent.
 10. The system of claim 8, wherein the operations furthercomprise determining a trace as the mechanical component.
 11. The systemof claim 8, wherein the operations further comprise determining acharacter as the mechanical component.
 12. The system of claim 8,wherein the operations further comprise determining a combination ofcharacters as the mechanical component.
 13. The system of claim 8,wherein the operations further comprise determining a letter as themechanical component.
 14. The system of claim 8, wherein the operationsfurther comprise determining a stroke as the mechanical component.
 15. Acomputer readable memory storing instructions that when executed cause aprocessor to perform operations, the operations comprising: receiving aninput sent from a device for authentication; segregating the input intoan image of a fingerprint and a mechanical component; determining amatch between the image of the fingerprint and a template for theauthentication; determining the match between the mechanical componentand the template for the authentication; and authenticating the devicein response to the match.
 16. The memory of claim 15, wherein theoperations further comprise determining a password as the mechanicalcomponent.
 17. The memory of claim 15, wherein the operations furthercomprise determining a trace as the mechanical component.
 18. The memoryof claim 15, wherein the operations further comprise determining acharacter as the mechanical component.
 19. The memory of claim 15,wherein the operations further comprise determining a combination ofcharacters as the mechanical component.
 20. The memory of claim 15,wherein the operations further comprise determining a letter as themechanical component.